{"title":"基于不变矩的形状识别算法的硬件实现","authors":"Clement Raffaitin, J. Romero, L. Prócel","doi":"10.1145/3338852.3339872","DOIUrl":null,"url":null,"abstract":"The present work shows the description of a simple fast shape detection algorithm and its implementation in hardware in a FPGA system. The detection algorithm is based on the concepts of Hús moments which are invariant to similarity transformations. The recognition algorithm is implemented by using a non-local means filter. The algorithm is implemented on a FPGA system by using a hardware description language. We present the different design stages of the algorithm implementation which is based on the finite state machine technique. This algorithm is able to recognize a target shape over a test image. Furthermore, this work, describes the advantages of the implementation in hardware, such as speed and parallelism in signal processing. Finally, we show some results of the implementation of this algorithm.","PeriodicalId":184401,"journal":{"name":"2019 32nd Symposium on Integrated Circuits and Systems Design (SBCCI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Hardware Implementation of a Shape Recognition Algorithm based on Invariant Moments\",\"authors\":\"Clement Raffaitin, J. Romero, L. Prócel\",\"doi\":\"10.1145/3338852.3339872\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The present work shows the description of a simple fast shape detection algorithm and its implementation in hardware in a FPGA system. The detection algorithm is based on the concepts of Hús moments which are invariant to similarity transformations. The recognition algorithm is implemented by using a non-local means filter. The algorithm is implemented on a FPGA system by using a hardware description language. We present the different design stages of the algorithm implementation which is based on the finite state machine technique. This algorithm is able to recognize a target shape over a test image. Furthermore, this work, describes the advantages of the implementation in hardware, such as speed and parallelism in signal processing. Finally, we show some results of the implementation of this algorithm.\",\"PeriodicalId\":184401,\"journal\":{\"name\":\"2019 32nd Symposium on Integrated Circuits and Systems Design (SBCCI)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-08-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 32nd Symposium on Integrated Circuits and Systems Design (SBCCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3338852.3339872\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 32nd Symposium on Integrated Circuits and Systems Design (SBCCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3338852.3339872","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Hardware Implementation of a Shape Recognition Algorithm based on Invariant Moments
The present work shows the description of a simple fast shape detection algorithm and its implementation in hardware in a FPGA system. The detection algorithm is based on the concepts of Hús moments which are invariant to similarity transformations. The recognition algorithm is implemented by using a non-local means filter. The algorithm is implemented on a FPGA system by using a hardware description language. We present the different design stages of the algorithm implementation which is based on the finite state machine technique. This algorithm is able to recognize a target shape over a test image. Furthermore, this work, describes the advantages of the implementation in hardware, such as speed and parallelism in signal processing. Finally, we show some results of the implementation of this algorithm.